![Sample our Earth Sciences journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5930/TOC-Subject-Sample-2021-Earth-Sciences.jpg"})
Abstract
The spatial distribution of wind speed is important information required to understand climate-related regional phenomena. This paper presents the Modified Korean Parameter-elevation Regression on Independent Slopes Model (MK-PRISM) as a method for spatial interpolation of monthly wind speeds. A database of gridded monthly mean wind speeds with a spatial resolution of 1 km for the period of March 2011–February 2014 is constructed by MK-PRISM. Wind speed observation data collected from the 529 to 641 meteorological stations in South Korea were utilized as the input data for interpolation. The wind speed distribution estimated by co-kriging is used for comparison with the MK-PRISM results. Research demonstrates that the efficiency difference between the two models, MK-PRISM and co-kriging, is insignificant. The Kling and Gupta efficiencies of both models were 0.68-0.78 and the root mean square errors (RMSEs) were 0.44-0.68 m/s. The spatial distribution of wind speeds, however, differs between MK-PRISM and co-kriging, which can be considered a reflection of the influence of topographic features such as terrain convexity, aspect, and coastal proximity. MK-PRISM can perform more appropriately to represent the phenomena where similar wind speeds appear continuously along ridges and coastlines. This suggests that a knowledge-based approach that considers topographic features can be successfully applied to the interpolation of monthly or seasonal wind speeds, similar to temperature and precipitation. The wind speed distribution generated by MK-PRISM can be utilized as important data for different geographical studies.
Acknowledgment
This work was supported by the research grant of the Kongju National University in 2014.
Disclosure statement
No potential conflict of interest was reported by the authors.